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The automatic generation of computer programs is one of the main applications with practical relevance in the field of evolutionary computation. With program synthesis techniques not only software developers could be supported in their…

Neural and Evolutionary Computing · Computer Science 2021-08-30 Dominik Sobania , Dirk Schweim , Franz Rothlauf

Machine learning (ML) is revolutionising drug discovery by expediting the prediction of small molecule properties essential for developing new drugs. These properties -- including absorption, distribution, metabolism and excretion (ADME)--…

Machine Learning · Computer Science 2024-08-02 Alex G. C. de Sá , David B. Ascher

Genomic data I used in many fields but, it has become known that most of the platforms used in the sequencing process produce significant errors. This means that the analysis and inferences generated from these data may have some errors…

Genomics · Quantitative Biology 2024-09-05 Ferdinand Kartriku , Robert Sowah , Charles Saah

To uncover the genetic basis of complex disease, individuals are often measured at a large number of genetic variants (usually SNPs) across the genome. GemTools provides computationally efficient tools for modeling genetic ancestry based on…

Applications · Statistics 2011-04-07 Lambertus Klei , Brian P. Kent , Nadine Melhem , Bernie Devlin , Kathryn Roeder

In microarray experiments, it is often of interest to identify genes which have a pre-specified gene expression profile with respect to time. Methods available in the literature are, however, typically not stringent enough in identifying…

Applications · Statistics 2009-01-18 J. Tuke , G. F. V. Glonek , P. J. Solomon

Motivation: Laboratory gene regulatory data for a species are sporadic. Despite the abundance of gene regulatory network algorithms that employ single data sets, few algorithms can combine the vast but disperse sources of data and extract…

Genomics · Quantitative Biology 2020-08-17 Mehrzad Saremi , Maryam Amirmazlaghani

The problem of multilabel classification when the labels are related through a hierarchical categorization scheme occurs in many application domains such as computational biology. For example, this problem arises naturally when trying to…

Machine Learning · Computer Science 2012-05-14 Sara Mostafavi , Quaid Morris

Proper naming of methods can make program code easier to understand, and thus enhance software maintainability. Yet, developers may use inconsistent names due to poor communication or a lack of familiarity with conventions within the…

Software Engineering · Computer Science 2023-08-25 Kisub Kim , Xin Zhou , Dongsun Kim , Julia Lawall , Kui Liu , Tegawendé F. Bissyandé , Jacques Klein , Jaekwon Lee , David Lo

We have micromachined a silicon-chip device that transports DNA with a Brownian ratchet that rectifies the Brownian motion of microscopic particles. Transport properties for a DNA 50mer agree with theoretical predictions, and the DNA…

Repetitive DNA (repeats) poses significant challenges for accurate and efficient genome assembly and sequence alignment. This is particularly true for metagenomic data, where genome dynamics such as horizontal gene transfer, gene…

Machine Learning · Computer Science 2024-02-15 Ali Azizpour , Advait Balaji , Todd J. Treangen , Santiago Segarra

Multi-label classification is an important yet challenging task in natural language processing. It is more complex than single-label classification in that the labels tend to be correlated. Existing methods tend to ignore the correlations…

Computation and Language · Computer Science 2018-06-18 Pengcheng Yang , Xu Sun , Wei Li , Shuming Ma , Wei Wu , Houfeng Wang

Microarray is a technology to quantitatively monitor the expression of large number of genes in parallel. It has become one of the main tools for global gene expression analysis in molecular biology research in recent years. The large…

Quantitative Methods · Quantitative Biology 2015-06-18 Min Xu

Consider a general machine learning setting where the output is a set of labels or sequences. This output set is unordered and its size varies with the input. Whereas multi-label classification methods seem a natural first resort, they are…

Machine Learning · Computer Science 2019-03-14 Tian Gao , Jie Chen , Vijil Chenthamarakshan , Michael Witbrock

Software Testing is a process to identify the quality and reliability of software, which can be achieved through the help of proper test data. However, doing this manually is a difficult task due to the presence of number of predicate nodes…

Software Engineering · Computer Science 2014-01-22 Yeresime Suresh , Santanu Ku. Rath

This paper presents EasyRAG, a simple, lightweight, and efficient retrieval-augmented generation framework for automated network operations. Our framework has three advantages. The first is accurate question answering. We designed a…

Computation and Language · Computer Science 2024-10-16 Zhangchi Feng , Dongdong Kuang , Zhongyuan Wang , Zhijie Nie , Yaowei Zheng , Richong Zhang

Deep learning, a rebranding of deep neural network research works, has achieved a remarkable success in recent years. With multiple hidden layers, deep learning models aim at computing the hierarchical feature representations of the…

Neural and Evolutionary Computing · Computer Science 2018-06-06 Jiawei Zhang , Limeng Cui , Fisher B. Gouza

We propose a dynamic neighborhood aggregation (DNA) procedure guided by (multi-head) attention for representation learning on graphs. In contrast to current graph neural networks which follow a simple neighborhood aggregation scheme, our…

Machine Learning · Computer Science 2019-04-16 Matthias Fey

Searching for similar genomic sequences is an essential and fundamental step in biomedical research and an overwhelming majority of genomic analyses. State-of-the-art computational methods performing such comparisons fail to cope with the…

Data Structures and Algorithms · Computer Science 2024-07-11 Mohammed Alser , Julien Eudine , Onur Mutlu

LAGE is a systematic framework developed in Java. The motivation of LAGE is to provide a scalable and parallel solution to reconstruct Gene Regulatory Networks (GRNs) from continuous gene expression data for very large amount of genes. The…

Machine Learning · Computer Science 2012-11-12 Yang Lu , Mengying Wang , Kenny Q. Zhu , Bo Yuan

Since microRNAs (miRNAs) play a crucial role in post-transcriptional gene regulation, miRNA identification is one of the most essential problems in computational biology. miRNAs are usually short in length ranging between 20 and 23 base…

Machine Learning · Computer Science 2016-05-04 Seunghyun Park , Seonwoo Min , Hyunsoo Choi , Sungroh Yoon
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